Amazon
Data Engineer II, AWS Marketing Insights
Amazon, Seattle, Washington, us, 98127
Description
Sales, Marketing and Global Services (SMGS)
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.
Amazon Web Services (AWS), a subsidiary of Amazon.com and a leader in cloud computing, is seeking a talented and experienced Data Engineer to join our AWS Marketing Insights team. In this pivotal role, you will be responsible for designing, building, and maintaining robust data pipelines and data infrastructure to support data-driven insights across the organization.
Key job responsibilities
As a Data Engineer on the AWS Marketing Insights team, your pivotal role will revolve around designing, building, and maintaining robust data pipelines and infrastructure to drive data-driven insights. Core responsibilities include architecting scalable and fault-tolerant pipelines to extract, transform, and load data from various sources into data warehouses or lakes. Leveraging cutting-edge tools and technologies, you'll implement ingestion, transformation, and integration processes, ensuring stringent data quality through validation, cleansing, and deduplication.
You'll design and implement high-performance, scalable, and cost-efficient data storage solutions. Utilizing CI/CD principles, you'll automate infrastructure deployment and maintenance processes, ensuring a streamlined data ecosystem. Data modeling and engineering will be crucial, involving designing and implementing optimized data models, developing and maintaining ETL processes, and collaborating with analysts and functional managers to understand data needs and provide tailored data structures.
Ensuring data governance, security, and compliance will be paramount. You'll implement robust policies and processes, enforce access controls, encryption, and auditing mechanisms, and collaborate cross-functionally to establish and maintain data governance standards.
Continuous improvement and automation will be woven into your daily activities, continuously evaluating and optimizing processes, pipelines, and infrastructure, implementing automation and monitoring tools, and staying ahead of emerging data engineering technologies and trends.
About the team
ABOUT AWS:
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Basic Qualifications
3+ years of data engineering experience
Experience with data modeling, warehousing and building ETL pipelines
Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
Knowledge of distributed systems as it pertains to data storage and computing
Experience with SQL
Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
Preferred Qualifications
Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
Experience building world-class data environments with a high emphasis on data quality and data security
Strong problem-solving and analytical skills, with the ability to translate business requirements into technical solutions
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,900/year in our lowest geographic market up to $205,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Sales, Marketing and Global Services (SMGS)
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.
Amazon Web Services (AWS), a subsidiary of Amazon.com and a leader in cloud computing, is seeking a talented and experienced Data Engineer to join our AWS Marketing Insights team. In this pivotal role, you will be responsible for designing, building, and maintaining robust data pipelines and data infrastructure to support data-driven insights across the organization.
Key job responsibilities
As a Data Engineer on the AWS Marketing Insights team, your pivotal role will revolve around designing, building, and maintaining robust data pipelines and infrastructure to drive data-driven insights. Core responsibilities include architecting scalable and fault-tolerant pipelines to extract, transform, and load data from various sources into data warehouses or lakes. Leveraging cutting-edge tools and technologies, you'll implement ingestion, transformation, and integration processes, ensuring stringent data quality through validation, cleansing, and deduplication.
You'll design and implement high-performance, scalable, and cost-efficient data storage solutions. Utilizing CI/CD principles, you'll automate infrastructure deployment and maintenance processes, ensuring a streamlined data ecosystem. Data modeling and engineering will be crucial, involving designing and implementing optimized data models, developing and maintaining ETL processes, and collaborating with analysts and functional managers to understand data needs and provide tailored data structures.
Ensuring data governance, security, and compliance will be paramount. You'll implement robust policies and processes, enforce access controls, encryption, and auditing mechanisms, and collaborate cross-functionally to establish and maintain data governance standards.
Continuous improvement and automation will be woven into your daily activities, continuously evaluating and optimizing processes, pipelines, and infrastructure, implementing automation and monitoring tools, and staying ahead of emerging data engineering technologies and trends.
About the team
ABOUT AWS:
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Basic Qualifications
3+ years of data engineering experience
Experience with data modeling, warehousing and building ETL pipelines
Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
Knowledge of distributed systems as it pertains to data storage and computing
Experience with SQL
Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
Preferred Qualifications
Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
Experience building world-class data environments with a high emphasis on data quality and data security
Strong problem-solving and analytical skills, with the ability to translate business requirements into technical solutions
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,900/year in our lowest geographic market up to $205,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.